Over the last decade, Bayesian inference has become
one of the most prevalent inferring instruments for a variety of disciplines,
including the computational statistics and statistical learning [1]}.
In general, Bayesian inference seeks to generate samples of the posterior
distribution of the form:
\(\rho (\mathrm {x})=\mathrm {e}^{-U(x)}/\int _{R^{d}}\mathrm {e}^{-U(y)}\mathrm {d}y,\) 
